Welcome

Welcome to EPsy 8251: Methods in Data Analysis for Educational Research I. This is the first course of a two-semester statistical methods sequence for doctoral students in education.

Instructor

Andrew Zieffler (zief0002@umn.edu)
Office: Education Sciences Building 178
Office Hours: Tuesday 9:00 AM–10:00 AM; and by appointment

Teaching Assistant

Mireya Smith (mart1799@umn.edu)
Office: Education Sciences Building 192
Office Hours: Thursdays 9:00 AM–11:00 AM; and by appointment

Classroom

Monday/Wednesday (2:30–3:45): Ford Hall 150
Tuesday/Thursday (11:15–12:30): Ford Hall B15

Course Content and Syllabus

The statistical content for EPsy 8251 includes rigorous coverage of estimation and hypothesis testing with a particular focus on ANOVA and multiple linear regression.

The course syllabus is available here.

Textbooks

The primary course textbook is available via the University of Minnesota library.

Applied regression: An introduction [required]

The secondary course textbook (available via Amazon) is

Presenting your findings: A practical guide for creating tables [required]

Schedule

Below is the tenative schedule for the class. The dates are subject to change at the instructor’s discretion. Readings should be completed prior to class.

Calendar

	T/R	M/W	Topic
	Sept. 03	Sept. 04	Welcome to EPsy 8251
Unit 01: Introduction to Statistical Computing
	Sept. 05	Sept. 09	Introduction to R and RStudio
	Sept. 10	Sept. 11	Data Wrangling with dplyr
	Sept. 12	Sept. 16	Plotting with ggplot2
Unit 02: Introduction to Linear Regression
	Sept. 17	Sept. 18	Simple Linear Regression: Description [Notes and script file updated 09-24-2019]
	Sept. 19	Sept. 23
	Sept. 24	Sept. 25	Least Squares Estimation [Notes and Script file updated 09-24-2019]
	Sept. 26	Sept. 30
	Sept. 26	Sept. 30	Correlation and Standardized Regression
	Oct. 01	Oct. 02	Correlation and Standardized Regression
Unit 04: Statistical Uncertainty and Inference
	Oct. 03	Oct. 07	Coefficient-Level Inference
	Oct. 08	Oct. 09	Coefficient-Level Inference
	Oct. 10	Oct. 14	Model-Level Inference
	Oct. 15	Oct. 26	Model-Level Inference
Unit 04: Multiple Linear Regression and Statistical Control
	Oct. 17	Oct. 21	Introduction to Multiple Linear Regression
	Oct. 22	Oct. 23	Introduction to Multiple Linear Regression
	Oct. 24	Oct. 28	Understanding Statistical Control
	Oct. 29	Oct. 30	Understanding Statistical Control
Unit 05: Model Assumptions
	Oct. 31	Nov. 04	Assumptions of the Regression Model
	Nov. 05	Nov. 06	Assumptions of the Regression Model
Unit 06: Categorical Predictors
	Nov. 07	Nov. 11	Dummy Coding Categorical Predictors
	Nov. 12	Nov. 13	Dummy Coding Categorical Predictors
	Nov. 14	Nov. 18	Effects Coding Categorical Predictors

Assignments

Below are the due dates for the assignments, as well as links to the RMD and PDF files for each assignment. The due dates may change at the instructor’s discretion. Any revised due dates will be announced in class and posted to the website.

Assignment	Due Date (T/R)	Due Date (M/W)
Assignment #1: Introduction to Statistical Computing [Updated 09-09-2019]	Sept. 19	Sept. 23
Assignment #2: Simple Regression: Description	Oct. 01	Oct. 02
Assignment #3: Correlation and Standardized Regression	Oct. 10	Oct. 14
Assignment #4: Simple Regression: Inference [Updated 09-09-2019]	Oct. 22	Oct. 23
Assignment #5: Introduction to Multiple Regression	Oct. 31	Nov. 04
Assignment #6: Regression Assumptions	Nov. 12	Nov. 13

Data

Below are the links to the data sets and data codebooks used in the notes, scripts, and assignments.

Name	Data	Codebook
evaluations.csv
fertility.csv
goodreads.csv
keith-gpa.csv
mn-schools.csv
riverview.csv
state-education.csv
waffle-house.csv